Tweets sent by the same person within a 4 hour time-window were used as samples of speed and direction. These samples were used to construct a vector field representing the average flow of people within the area. The vector field and total tweet density over the space were then used to simulate the movement of people. Particles, representing people, were released at locations where actual tweets were recorded and their subsequent movement was determined by the flow field. The particles start out blue and gradually change through purple to red over time so each trace shows the direction of movement. Locations where there is little movement will have blue dots or very short blue traces. Longer traces with more red show a greater speed at that point.
Movement in Manhattan based on tweets. Complement with some deliciously analog, subjective, hand-drawn maps of Manhattan.




